Abstract
The advancement in battery manufacturing has played a significant role in the use of batteries as a cost-effective energy storage system. This paper proposes an optimal charging and discharging strategy for the battery energy storage system deployed for economic dispatch and supply/demand balancing services in the presence of intermittent renewables such as solar photovoltaic systems. A decision-making strategy for battery charge/discharge operations in a discrete-time rolling horizon framework is developed as a finite-input set non-linear model predictive control instances and a dynamic programming procedure is proposed for its real-time implementation. The proposed scheme is tested on controllable loads and a photovoltaic generation scenario in the premises of a sports centre, as a part of a pilot demonstration of the inteGRIDy EU-funded project. The test results confirm that the implemented stacking of the battery and optimal decision-making algorithm can enhance net saving in the electricity bill of the sports centre, and lead to corresponding CO2 reductions.
Highlights
IntroductionBattery energy storage systems (BESS) have gained continuous research attention due to these features and given substantial advancement in battery technologies and increasing decentralisation of grid operations, localised controls are receiving much attention [2,3]
To progress beyond a laboratory prototype, the technique has been implemented, tested, and validated in the premises of a sports centre located at Rambla del Celler, in Sant Cugat, Barcelona, as a part of a pilot demonstration of the inteGRIDy EU-funded project
Our findings indicate that (i) the proposed technique is simple enough to be implemented on resource-constrained field devices and operate with required sample times for typical Battery energy storage systems (BESS) requirements, and that (ii) the algorithm implementation achieved non-trivial reductions (≈15%) in energy costs and CO2 emissions
Summary
BESS have gained continuous research attention due to these features and given substantial advancement in battery technologies and increasing decentralisation of grid operations, localised controls are receiving much attention [2,3]. This has resulted in the introduction of various battery control and management algorithms, and led to the development of batteries with an increased capacity-to-size ratio featuring faster charging and discharging rates, longer life spans and relatively lower prices [2,4,5]. There have been many developments in research in these areas, to date there has been, with some exceptions, a noticeable lack of technology transfer beyond laboratory prototypes and into real-world implementations of more advanced sensing, estimation, and charge controls for BESS [2]
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